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    This study introduces a method to analyze lensless single random phase encoding (SRPE) systems, finding they are robust to image sensor pixel size variations. This work provides a formula to optimize SRPE systems for accurate signal capture.

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    Area of Science:

    • Optics and Photonics
    • Image Processing
    • Computational Imaging

    Background:

    • Lensless single random phase encoding (SRPE) systems modulate optical fields using diffusers before intensity capture.
    • Conventional sampling criteria are insufficient for SRPE systems due to inherent high spatial frequencies from diffusers.

    Purpose of the Study:

    • To develop a procedure for analyzing the robustness of lensless SRPE systems to image sensor pixel size variations.
    • To establish a theoretical estimate for the maximum sensor pixel size that accurately captures input signal frequencies in lensless SRPE systems.

    Main Methods:

    • Wave propagation analysis to estimate maximum pixel size for accurate intensity pattern capture.
    • Numerical simulations using angular spectrum propagation and mutual information to verify theoretical estimates.
    • Development of a closed-form estimate for maximum sensor pixel size based on input frequency and system parameters.

    Main Results:

    • A theoretical estimate for the upper limit of image sensor pixel size was proposed.
    • Numerical simulations closely matched the theoretical estimates for the sampling criterion.
    • Lensless SRPE systems demonstrate significantly higher robustness to sensor pixel size compared to lens-based systems.

    Conclusions:

    • The proposed method provides a reliable theoretical estimate for optimizing general-purpose SRPE systems.
    • Lensless SRPE systems are advantageous for applications with large pixel sizes, such as exotic imagers.
    • This research is the first to investigate SRPE system sampling concerning input frequency and physical parameters to determine maximum sensor pixel size.